easysnowdata.climate.indices.seasonal_mean#

easysnowdata.climate.indices.seasonal_mean(obj: Dataset | DataArray | Series | DataFrame, months: tuple[int, ...] = (11, 12, 1, 2, 3), *, hemisphere: str = 'northern', min_months: int | None = None) → DataFrame[source]#

Average each index over months, one row per water year.

The default, November-March, is the accumulation season most snowpack teleconnection studies use. Months are assigned to the water year they fall in (easysnowdata.processing.wateryear.water_year()), so a December-February window is one row, not two.

Parameters:

  • obj – The output of load(), one of its variables, or a pandas Series/DataFrame on a DatetimeIndex.

  • months – Calendar months to average.

  • hemisphere – Water-year convention ("northern" starts in October).

  • min_months – Years with fewer valid months than this are NaN (default: all of months, so a season still in progress is not reported).

Returns:

pandas.DataFrame – Index water_year; one column per index.

Examples using easysnowdata.climate.indices.seasonal_mean#

Climate-mode indices: PDO, ENSO, AO (NOAA NCEI / CPC / PSL)

Climate-mode indices: PDO, ENSO, AO (NOAA NCEI / CPC / PSL)